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Oliver C. Stringham
PhD, Data Scientist & Scientific Researcher
I apply scientific rigor and curiosity to solving data science problems.
Professional Experience
Data Scientist
Freelance (UpWork & Contract Work)
USA & Australia
2020 - present
- Machine Learning models to predict daily number of orders for retail company
- Spatial optimization to determine zones for delivery trucks
- Spatial clustering methods to categorize property evaluation
- Quantitative analysis of country-level deforestation rates from spatial data
Research Associate (Postdoctoral)
The University of Adelaide
Adelaide, Australia
2019 - present
- Applied data science principles to researching wildlife trade
- Coded over 80 webscrapers to collect data of online wildlife trade
- Created/maintained MySQL database of >6 million records for wildlife trade
- Machine learning tools (text classification) to process online data
- Created web application with python (Flask) for Australian gov’t
- Communicated results in reports, papers, and talks
- Supervised and lead a team of skilled professionals
PhD Researcher & Teaching Assistant
Rutgers University
New Jersey, USA
2015 - 2018
- Researched the online pet trade of reptiles and their invasion risk
- Taught courses: General Biology, Ornithology, Plant Ecology
- Worked in an interdisciplinary international team of scientists
Geospatial (GIS) Technician
New Jersey Depart. of Fish & Wildlife
New Jersey, USA
2015
- Performed geospatial analyses for endangered species programs
- Used python to automate geospatial processes previously done manually
Geospatial (GIS) Analyst
Harbor & Estuary Program, Hudson River Foundation
New York, USA
2015
- Performed spatial analyses regarding public access to waterways in NYC/NJ
Education
Rutgers University
PhD in Ecology & Evolution
New Jersey, USA
2018
Rutgers University
BS in Environmental Science
Certificate in GIS (Geographic Information Systems)
New Jersey, USA
2014
Technical Papers
Text classification to streamline online wildlife trade analyses
PLOS ONE
N/A
2021
A guide to using the internet to study the wildlife trade
Conservation Biology
N/A
2020